Merge pull request #24 from bricksdont/read_only_option

fix(reader): make array writeable by default

pose_format/utils/reader.py

@@ -33,15 +33,15 @@ def unpack_f(self, s_format: str):
         return self.unpack(getattr(ConstStructs, s_format))
 
     def unpack_numpy(self, s: struct.Struct, shape: Tuple):
-        arr = np.ndarray(shape, s.format, self.buffer, self.read_offset)
+        arr = np.ndarray(shape, s.format, self.buffer, self.read_offset).copy()
         self.advance(s, int(np.prod(shape)))
         return arr
 
     def unpack_torch(self, s: struct.Struct, shape: Tuple):
         import torch
 
-        arr = self.unpack_numpy(s, shape)  # Array is not writable
-        return torch.from_numpy(np.array(arr))
+        arr = self.unpack_numpy(s, shape)
+        return torch.from_numpy(arr)
 
     def unpack_tensorflow(self, s: struct.Struct, shape: Tuple):
         import tensorflow as tf

pose_format/utils/reader_test.py

@@ -51,6 +51,16 @@ def test_unpack_numpy(self):
         res = np.array([[1., 2.5], [3.5, 4.5]])
         self.assertTrue(np.all(arr == res), msg="Numpy unpacked array is not equal to expected array")
 
+    def test_unpack_numpy_writeable(self):
+        buffer = struct.pack("<ffff", 1., 2.5, 3.5, 4.5)
+        reader = BufferReader(buffer)
+
+        arr = reader.unpack_numpy(ConstStructs.float, (2, 2))
+
+        # if array is read-only, this will raise a ValueError
+
+        arr -= 0.1
+
     def test_unpack_torch(self):
         buffer = struct.pack("<ffff", 1., 2.5, 3.5, 4.5)
         reader = BufferReader(buffer)

setup.py

@@ -11,7 +11,7 @@
 setup(
   name='pose_format',
   packages=packages,
-  version='0.1.0',
+  version='0.1.1',
   description='Library for viewing, augmenting, and handling .pose files',
   author='Amit Moryossef',
   author_email='amitmoryossef@gmail.com',